End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: JackFram/llama-160m
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: 96539b3d-465e-4ead-a68e-d0f8380df2ed
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.1`
+```yaml
+adapter: lora
+base_model: JackFram/llama-160m
+bf16: true
+chat_template: llama3
+datasets:
+- data_files:
+  - b12005b8824189e8_train_data.json
+  ds_type: json
+  format: custom
+  path: /workspace/input_data/b12005b8824189e8_train_data.json
+  type:
+    field_instruction: title
+    field_output: keywords
+    format: '{instruction}'
+    no_input_format: '{instruction}'
+    system_format: '{system}'
+    system_prompt: ''
+debug: null
+deepspeed: null
+early_stopping_patience: null
+eval_max_new_tokens: 128
+eval_table_size: null
+evals_per_epoch: 4
+flash_attention: true
+fp16: false
+fsdp: null
+fsdp_config: null
+gradient_accumulation_steps: 2
+gradient_checkpointing: true
+group_by_length: false
+hub_model_id: sn5601/96539b3d-465e-4ead-a68e-d0f8380df2ed
+hub_repo: null
+hub_strategy: checkpoint
+hub_token: null
+learning_rate: 0.0001
+load_in_4bit: false
+load_in_8bit: false
+local_rank: null
+logging_steps: 1
+lora_alpha: 32
+lora_dropout: 0.05
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 16
+lora_target_linear: true
+lr_scheduler: cosine
+max_memory:
+  0: 77GiB
+max_steps: 100
+micro_batch_size: 8
+mlflow_experiment_name: /tmp/b12005b8824189e8_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 3
+optimizer: adamw_torch
+output_dir: miner_id_24
+pad_to_sequence_len: true
+resume_from_checkpoint: null
+s2_attention: null
+sample_packing: false
+save_steps: 25
+save_strategy: steps
+sequence_len: 1024
+special_tokens:
+  pad_token: </s>
+strict: false
+tf32: false
+tokenizer_type: AutoTokenizer
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 0.05
+wandb_entity: sn56-miner
+wandb_mode: disabled
+wandb_name: 96539b3d-465e-4ead-a68e-d0f8380df2ed
+wandb_project: god
+wandb_run: your_name
+wandb_runid: 96539b3d-465e-4ead-a68e-d0f8380df2ed
+warmup_steps: 10
+weight_decay: 0.01
+xformers_attention: false
+
+```
+
+</details><br>
+
+# 96539b3d-465e-4ead-a68e-d0f8380df2ed
+
+This model is a fine-tuned version of [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.2420
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 64
+- total_eval_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- training_steps: 100
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 5.5006        | 0.0058 | 1    | 5.9769          |
+| 5.5759        | 0.0519 | 9    | 5.7626          |
+| 5.0034        | 0.1037 | 18   | 4.9021          |
+| 4.3982        | 0.1556 | 27   | 4.3000          |
+| 3.8321        | 0.2075 | 36   | 3.7707          |
+| 3.4402        | 0.2594 | 45   | 3.5292          |
+| 3.291         | 0.3112 | 54   | 3.4005          |
+| 3.1737        | 0.3631 | 63   | 3.3237          |
+| 3.3567        | 0.4150 | 72   | 3.2791          |
+| 3.2126        | 0.4669 | 81   | 3.2543          |
+| 3.1963        | 0.5187 | 90   | 3.2445          |
+| 3.0855        | 0.5706 | 99   | 3.2420          |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.46.0
+- Pytorch 2.5.0+cu124
+- Datasets 3.0.1
+- Tokenizers 0.20.1

adapter_model.bin

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